In an imaging label scanner, such as a barcode scanner, one problem that exists is that full labels with barcodes or other indicia (e.g., QR codes) are not always seen by imagers due to label folding, distortion, specular reflection, camera orientation, etc. As such, label stitching, as understood in the art, may be utilized to improve the reading of labels. For accuracy and error reduction purposes, label stitching overlaps multiple characters since segments of labels can be captured from different labels on one or more products in a field-of-view of imaging cameras. For automated barcode scanners, such as Jade X7™ produced by Datalogic ADC, Inc, the stitching success rate is lower than commercially possible since items pass through a scanning portal only once, and no human intervention (e.g., rescanning) is possible to correct for a scanning misread or no read.
Another problem that exists with label scanners is that simplified item computer modeling, such as modeling items as cylinders and rectangular boxes, may be used for automated scanners. Item modeling may use a maximum height and width as a rectangular box height and width so that label strike calculations of one item can be blocked by a rectangular box from another item using simplified modeling. However, misalignment due to camera “see-through” may cause a barcode affixed to a second item positioned behind a first item being scanned that results in the label or segments of the labels being applied to the first item being scanned, thereby causing a label to assigned to a wrong item or an error in the label scanning process. Accordingly, there is a need to improve a label scanning and reading of automated label readers.